hippox 0.6.0

🔗 Quick Links

Basic Usage

Instantiate

// =================== Method 1 ===================
let hippox = Hippox::builder(ModelProvider::OpenAI)
    .api_key("sk-xxx")
    .lang("zh")
    .identity(|id| {
        id.name = Some("agent".to_string());
        id.role = Some("assistant".to_string());
        id.personality = Some("friendly".to_string());
    })
    .build()
    .await?;

// =================== Method 2 ===================
let mut config = HippoxConfig::default();
config.lang = "zh".to_string();
config.identity_information = IdentityInformation {
    name: Some("agent".to_string()),
    role: Some("assistant".to_string()),
    personality: Some("friendly".to_string()),
    ..Default::default()
};
let hippox = Hippox::new(
    ModelProvider::OpenAI,
    Some("sk-xxx".to_string()),
    None,
    Some(config),
).await?;

// =================== Simple Method ===================
let hippox = Hippox::new(
    ModelProvider::OpenAI,
    Some("sk-xxx".to_string()),
    None,
    Some(HippoxConfig::default()),
).await?;

// builder
let hippox = Hippox::builder(ModelProvider::OpenAI)
    .api_key("sk-xxx")
    .build()
    .await?;

Task Execution

Submit

1. Execution mode

• Asynchronous non-blocking submission. Task goes to background pool, returns task_id immediately. Result must be obtained via polling.

2. How it works

• Call submit() method
• NaturalLanguageTask is created and pushed to global TASK_POOL
• Background execution engine processes tasks automatically
• Method returns task_id immediately (does NOT wait for completion)
• Caller repeatedly queries get_task(task_id) to check status
• When task.status == TaskStatus::Completed, extract result from task.final_output

3. Use when

• You don't need immediate results, or want to run multiple tasks concurrently.

use hippox::{Hippox, TaskStatus};
use langhub::types::ModelProvider;
use std::time::Duration;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let hippox = Hippox::builder(ModelProvider::OpenAI)
        .api_key("sk-xxx")
        .build()
        .await?;
    // Submit task, returns task_id immediately
    let task_id = hippox.submit("Calculate 15 * 3", None);
    let result = hippox.wait_task(&task_id).await?;
    println!("Result: {}", result);
    Ok(())
}

Execute - Direct execution

1. Execution mode

• Synchronous blocking call. The function waits until the task completes and returns the result directly.

2. How it works

• Call execute() method
• Task starts immediately in the current thread
• Code pauses and waits for completion
• Returns String result directly

3. Use when

• You need the result immediately and don't want to manage task state.

use hippox::Hippox;
use langhub::types::ModelProvider;

#[tokio::main]
async fn main() -> anyhow::Result<()> {
    let hippox = Hippox::builder(ModelProvider::OpenAI)
        .api_key("sk-xxx")
        .build()
        .await?;
    // Execute and wait for result
    let result = hippox.execute("Calculate 15 * 3", None).await;
    println!("Result: {}", result);
    Ok(())
}

Configuration

1. HippoxConfig

/// Hippox global configuration
#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
pub struct HippoxConfig {
    /// Language setting: "en" or "zh"
    pub lang: String,
    /// AI identity information (name, role, personality, etc.)
    pub identity_information: IdentityInformation,
}

2. IdentityInformation

/// AI identity configuration
#[derive(Debug, Clone, serde::Deserialize, serde::Serialize)]
pub struct IdentityInformation {
    /// AI name, e.g., "Assistant", "Hippox"
    pub name: Option<String>,
    /// Gender, e.g., "male", "female", "neutral"
    pub sex: Option<String>,
    /// Age, e.g., "25", "young"
    pub age: Option<String>,
    /// Species, e.g., "AI", "human", "robot"
    pub species: Option<String>,
    /// Role, e.g., "assistant", "teacher", "life coach"
    pub role: Option<String>,
    /// Personality, e.g., "friendly", "humorous", "professional"
    pub personality: Option<String>,
    /// Tone style, e.g., "casual", "formal", "poetic"
    pub tone_style: Option<String>,
    /// Knowledge scope, e.g., "general", "medical", "programming"
    pub knowledge_scope: Option<String>,
    /// Catchphrase, e.g., "Haha", "I see", "Let's go"
    pub catchphrase: Option<String>,
    /// Prohibited topics, e.g., "no politics", "no medical advice"
    pub taboos: Option<String>,
}

Hippox Core Working Principle

┌─────────────────────────────────────────────────────────────────────────────┐
│                        Hippox Core Working Principle                        │
├─────────────────────────────────────────────────────────────────────────────┤
│                                                                             │
│  ┌───────────────────────────────────────────────────────────────────────┐ │
│  │ 1. Task Submission (Non-blocking)                                     │ │
│  │    hippox.submit(input) → NaturalLanguageTask → TASK_POOL            │ │
│  │    → TASK_NOTIFIER.notify_one() → return task_id                     │ │
│  └───────────────────────────────────────────────────────────────────────┘ │
│                                      │                                      │
│                                      ▼                                      │
│  ┌───────────────────────────────────────────────────────────────────────┐ │
│  │ 2. Intent Analysis (Step 1)                                           │ │
│  │    build_intent_parser_prompt() → LLM.generate() → parse              │ │
│  │    Output: clean_intent, skill_categories                             │ │
│  └───────────────────────────────────────────────────────────────────────┘ │
│                                      │                                      │
│                                      ▼                                      │
│  ┌───────────────────────────────────────────────────────────────────────┐ │
│  │ 3. Workflow Execution (Step 2) using clean_intent                     │ │
│  │    ┌──────────┐ ┌──────────┐ ┌──────────┐ ┌─────────────────┐        │ │
│  │    │  ReAct   │ │  Batch   │ │  Chain   │ │ PlanAndExecute  │        │ │
│  │    └────┬─────┘ └────┬─────┘ └────┬─────┘ └───────┬─────────┘        │ │
│  │         └────────────┴────────────┴──────────────┘                   │ │
│  │    LLM generates SkillCall → Executor.execute() → raw_json           │ │
│  └───────────────────────────────────────────────────────────────────────┘ │
│                                      │                                      │
│                                      ▼                                      │
│  ┌───────────────────────────────────────────────────────────────────────┐ │
│  │ 4. Response Formatting (Step 3)                                       │ │
│  │    needs_format_conversion(original_input)?                           │ │
│  │    ┌─────────┐      ┌─────────────────────────────────────────────┐  │ │
│  │    │  false  │ ──▶ │  return raw_json directly                    │  │ │
│  │    └─────────┘      └─────────────────────────────────────────────┘  │ │
│  │    ┌─────────┐      ┌─────────────────────────────────────────────┐  │ │
│  │    │  true   │ ──▶ │  build_format_conversion_prompt()            │  │ │
│  │    └─────────┘      │  → LLM.generate() → formatted output        │  │ │
│  │                     └─────────────────────────────────────────────┘  │ │
│  └───────────────────────────────────────────────────────────────────────┘ │
│                                      │                                      │
│                                      ▼                                      │
│                              final_output                                   │
└─────────────────────────────────────────────────────────────────────────────┘

Pipe Line

User Input
    │
    ▼
┌─────────────┐
│   Step 1    │ → Intent Analysis
│   Analysis  │   build_intent_parser_prompt() → LLM
└──────┬──────┘   Output: clean_intent, skill_categories
       │
       ▼
┌─────────────┐
│   Step 2    │ → Workflow Execution
│  Execution  │   Execute skills using clean_intent
└──────┬──────┘   Output: raw_json
       │
       ▼
┌─────────────┐      ┌─────────────┐
│ Need Format │ ──Yes──▶│   Step 3    │ → Response Formatting
│ Conversion? │      │ Formatting  │   build_format_conversion_prompt() → LLM
└──────┬──────┘      └──────┬──────┘
       │                    │
       └──────────┬─────────┘
                  ▼
            Final Output

Task Pool

State Machine

Pending ──► Running ──► Completed
    │           │
    │           ├──► Paused ──► Running (resume)
    │           │
    │           └──► Cancelled
    │
    └──► Cancelled
              │
              └──► Failed ──► Pending (retry)

Architecture

┌─────────────────────────────────────────────────────────────────┐
│                      Global Static (Auto-Start)                 │
│  ┌───────────────────────────────────────────────────────────┐  │
│  │                    GLOBAL_TASK_POOL                        │  │
│  │              (Initialized at program load)                │  │
│  └───────────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                        Hippox Instance                          │
├─────────────────────────────────────────────────────────────────┤
│  ┌───────────────────────────────────────────────────────────┐  │
│  │                    TaskPool (Global)                       │  │
│  │  ┌─────────┐  ┌─────────┐  ┌─────────┐                   │  │
│  │  │Task A   │  │Task B   │  │Task C   │                   │  │
│  │  │Pending  │  │Running  │  │Pending  │                   │  │
│  │  └────┬────┘  └────┬────┘  └────┬────┘                   │  │
│  │       └────────────┼────────────┘                         │  │
│  │                    ▼                                      │  │
│  │         ┌─────────────────────┐                          │  │
│  │         │    Priority Queue   │                          │  │
│  │         │  [Task A, Task C]   │                          │  │
│  │         └──────────┬──────────┘                          │  │
│  │                    │                                      │  │
│  │                    ▼                                      │  │
│  │         ┌─────────────────────┐                          │  │
│  │         │  Execution Engine   │  (max: 10 workers)      │  │
│  │         │  ┌────┐ ┌────┐ ┌────┐                         │  │
│  │         │  │ W1 │ │ W2 │ │ W3 │  ...                    │  │
│  │         │  └──┬─┘ └──┬─┘ └──┬─┘                         │  │
│  │         │     └──────┼──────┘                           │  │
│  │         │           ▼                                   │  │
│  │         │  ┌─────────────────┐                          │  │
│  │         │  │ ExecutableTask  │                          │  │
│  │         │  │   .execute()    │                          │  │
│  │         │  └─────────────────┘                          │  │
│  │         └─────────────────────┘                          │  │
│  │                    ▲                                      │  │
│  │         ┌──────────┴──────────┐                          │  │
│  │         │  Notifier (wakeup)  │                          │  │
│  │         └─────────────────────┘                          │  │
│  └───────────────────────────────────────────────────────────┘  │
│                                                                  │
│  ┌───────────────────────────────────────────────────────────┐  │
│  │              ExecutableTask Implementation                │  │
│  │  ┌─────────────────────────────────────────────────────┐  │  │
│  │  │                  NaturalLanguageTask                │  │  │
│  │  │  • input: String                                    │  │  │
│  │  │  • workflow_executor: WorkflowExecutor              │  │  │
│  │  │  • scheduler: SkillScheduler                        │  │  │
│  │  └─────────────────────────────────────────────────────┘  │  │
│  └───────────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────────┘
                              │
                              ▼
┌─────────────────────────────────────────────────────────────────┐
│                         External APIs                           │
├─────────────────────────────────────────────────────────────────┤
│  handle_natural_language()  → task_id  (non-blocking)          │
│  get_task_status() / cancel() / pause() / resume() / retry()   │
└─────────────────────────────────────────────────────────────────┘

Workflow Model

Atomic Skill Registry

💡 Hint：In Hippox, an atomic skill represents a smallest indivisible unit of execution, This is a different concept from "Skill" in user business.

Working Principle

┌─────────────────────────────────────────────────────────────┐
│                      SKILL REGISTRY                        │
│                                                           │
│  SkillRegistryMap = HashMap<SkillCategory,               │
│                      HashMap<String, Arc<dyn Skill>>>    │
│                                                           │
│  ┌──────────┐  ┌──────────┐  ┌──────────┐              │
│  │ File     │  │ Math     │  │ Net      │              │
│  ├──────────┤  ├──────────┤  ├──────────┤              │
│  │ read     │  │ calc     │  │ http     │              │
│  │ write    │  │ power    │  │ ping     │              │
│  │ delete   │  │ stats    │  │ dns      │              │
│  │ ...      │  │ ...      │  │ ...      │              │
│  └──────────┘  └──────────┘  └──────────┘              │
└─────────────────────────────────────────────────────────────┘

Registration:

  Compile-time: file_register() / math_register() / net_register()
  Runtime: register_skill(category, name, skill)

Query:

  get_skill_by_name("read") → Skill impl → execute()

Core Type

pub type SkillRegistryMap = HashMap<SkillCategory, HashMap<String, Arc<dyn Skill>>>;

Main Functions

SkillCategory Methods